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Nationwide HVAC energy-saving potential quantification for office buildings with occupant-centric controls in various climates

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  • Pang, Zhihong
  • Chen, Yan
  • Zhang, Jian
  • O'Neill, Zheng
  • Cheng, Hwakong
  • Dong, Bing

Abstract

The occupant-centric control (OCC) is receiving an increasing attention since it could reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CPBM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis, which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones, was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in the majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode.

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  • Pang, Zhihong & Chen, Yan & Zhang, Jian & O'Neill, Zheng & Cheng, Hwakong & Dong, Bing, 2020. "Nationwide HVAC energy-saving potential quantification for office buildings with occupant-centric controls in various climates," Applied Energy, Elsevier, vol. 279(C).
    • Handle: RePEc:eee:appene:v:279:y:2020:i:c:s0306261920312186
    DOI: 10.1016/j.apenergy.2020.115727
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    References listed on IDEAS

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    1. Oldewurtel, Frauke & Sturzenegger, David & Morari, Manfred, 2013. "Importance of occupancy information for building climate control," Applied Energy, Elsevier, vol. 101(C), pages 521-532.
    2. Peng, Yuzhen & Rysanek, Adam & Nagy, Zoltán & Schlüter, Arno, 2018. "Using machine learning techniques for occupancy-prediction-based cooling control in office buildings," Applied Energy, Elsevier, vol. 211(C), pages 1343-1358.
    3. Naylor, Sophie & Gillott, Mark & Lau, Tom, 2018. "A review of occupant-centric building control strategies to reduce building energy use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 1-10.
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    Cited by:

    1. Dehwah, Ammar H.A. & Krarti, Moncef, 2022. "Optimal controls of precooling strategies using switchable insulation systems for commercial buildings," Applied Energy, Elsevier, vol. 320(C).
    2. Kong, Meng & Dong, Bing & Zhang, Rongpeng & O'Neill, Zheng, 2022. "HVAC energy savings, thermal comfort and air quality for occupant-centric control through a side-by-side experimental study," Applied Energy, Elsevier, vol. 306(PA).
    3. Alperen Yayla & Kübra Sultan Świerczewska & Mahmut Kaya & Bahadır Karaca & Yusuf Arayici & Yunus Emre Ayözen & Onur Behzat Tokdemir, 2022. "Artificial Intelligence (AI)-Based Occupant-Centric Heating Ventilation and Air Conditioning (HVAC) Control System for Multi-Zone Commercial Buildings," Sustainability, MDPI, vol. 14(23), pages 1-29, December.
    4. Yoon, Y. & Jung, S. & Im, P. & Salonvaara, M. & Bhandari, M. & Kunwar, N., 2023. "Empirical validation of building energy simulation model input parameter for multizone commercial building during the cooling season," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    5. Guanjing Lin & Armando Casillas & Maggie Sheng & Jessica Granderson, 2023. "Performance Evaluation of an Occupancy-Based HVAC Control System in an Office Building," Energies, MDPI, vol. 16(20), pages 1-21, October.
    6. Nilofar Asim & Marzieh Badiei & Masita Mohammad & Halim Razali & Armin Rajabi & Lim Chin Haw & Mariyam Jameelah Ghazali, 2022. "Sustainability of Heating, Ventilation and Air-Conditioning (HVAC) Systems in Buildings—An Overview," IJERPH, MDPI, vol. 19(2), pages 1-16, January.
    7. Wang, Junqi & Jiang, Lanfei & Yu, Hanhui & Feng, Zhuangbo & Castaño-Rosa, Raúl & Cao, Shi-jie, 2024. "Computer vision to advance the sensing and control of built environment towards occupant-centric sustainable development: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    8. Ye, Yunyang & Chen, Yan & Zhang, Jian & Pang, Zhihong & O’Neill, Zheng & Dong, Bing & Cheng, Hwakong, 2021. "Energy-saving potential evaluation for primary schools with occupant-centric controls," Applied Energy, Elsevier, vol. 293(C).
    9. Pang, Zhihong & O'Neill, Zheng & Chen, Yan & Zhang, Jian & Cheng, Hwakong & Dong, Bing, 2023. "Adopting occupancy-based HVAC controls in commercial building energy codes: Analysis of cost-effectiveness and decarbonization potential," Applied Energy, Elsevier, vol. 349(C).
    10. Yamaguchi, Yohei & Kim, Bumjoon & Kitamura, Takuya & Akizawa, Kotone & Chen, Hemiao & Shimoda, Yoshiyuki, 2022. "Building stock energy modeling considering building system composition and long-term change for climate change mitigation of commercial building stocks," Applied Energy, Elsevier, vol. 306(PA).
    11. Raman, Naren Srivaths & Chen, Bo & Barooah, Prabir, 2022. "On energy-efficient HVAC operation with Model Predictive Control: A multiple climate zone study," Applied Energy, Elsevier, vol. 324(C).

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